# Claude Opus 4.7 vs GLM-5.3

> Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 54.6 on the Noometry Index. GLM-5.3 costs 4.7× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/claude-opus-4-7-vs-glm-5-3
- Last updated: 2026-10-10
- Shared benchmarks: 38

## Summary

- They share 38 benchmarks with published results for both. Claude Opus 4.7 scores higher in 8 categories and GLM-5.3 in 1 category; 5 gaps are clear of the uncertainty.
- The widest gap is in agentic & tool use, where Claude Opus 4.7 leads 47.9 to 36.3.
- The biggest single-benchmark swing is NYT Connections (extended): 39% for Claude Opus 4.7 and 74.2% for GLM-5.3.
- GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $5 / $25 for Claude Opus 4.7.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| Provider | Anthropic | Z.ai (Zhipu) |
| Noometry Index | 58.4 | 54.6 |
| Rank | 17 | 25 |
| Context | 1M | 1M |
| Input $/M | $5 | $1.40 |
| Output $/M | $25 | $4.40 |
| Weights | Proprietary | Open |

## Coding

- Claude Opus 4.7: 59.9 (#10)
- GLM-5.3: 59.0 (#12)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| FrontierCode | 38.5% | 40.1% |
| LMArena WebDev | 1557 | 1623 |
| SciCode | 54.5% | 59% |
| WeirdML | 76.4% | 75.4% |
| LMArena Coding | 1519 | 1499 |
| ALE-Bench | 1,323 | 1,317 |
| SWE-bench Verified | 83.5% | — |
| DeepSWE | — | 69% |
| FrontierSWE | — | 30.2% |
| GSO | 44.1% | — |
| MirrorCode | 31.1% | — |

## Agentic & Tool Use

- Claude Opus 4.7: 47.9 (#8)
- GLM-5.3: 36.3 (#34)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| APEX-Agents | 49.2% | 56.6% |
| Vending-Bench 2 | 10,937 | 8,164 |
| Terminal-Bench | 80.2% | — |
| OSWorld 2.0 | 18.2% | — |
| τ²-bench Banking | 40.2% | — |
| PostTrainBench | 28.6% | — |
| ExploitBench | 26.5% | — |
| GBAEval | 43.8% | — |
| GDP.pdf | 21% | — |
| LMArena Search | 1233 | — |

## Reasoning

- Claude Opus 4.7: 53.7 (#24)
- GLM-5.3: 45.2 (#42)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| NYT Connections (extended) | 39% | 74.2% |
| CritPt | 12% | 19.1% |
| Chess Puzzles | 30% | 21% |
| LMArena Hard Prompts | 1507 | 1491 |
| Mystery Game Puzzles | 28% | 33% |
| DTBench | 94.7% | 87.7% |
| LMCA | 52.2% | 55.5% |
| Epoch Capabilities Index | 156.39 | 155.56 |
| ARC-AGI-2 | 75.8% | — |
| SimpleBench | 61.7% | — |
| Kagi LLM Benchmark | 80.7% | — |
| ARC-AGI-1 | 93.5% | — |
| Thematic Generalization | 72.8% | — |
| EBR-Bench | 19% | — |
| Bench to the Future 3 | — | 0.15 |
| ForecastBench | 60.3 | — |

## Math

- Claude Opus 4.7: 66.5 (#20)
- GLM-5.3: 62.1 (#27)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 70.2% | 68.8% |
| FrontierMath Tier 4 | 31.7% | 29.3% |
| OTIS Mock AIME 2024-2025 | 97.8% | 91.1% |
| ProofBench | 54% | 49% |
| LMArena Math | 1499 | 1493 |
| MathArena Final-Answer Competitions | 73.6% | — |
| FrontierMath (Feb 2025 set) | 43.8% | — |
| FrontierMath Tier 4 (v1) | 22.9% | — |

## Knowledge

- Claude Opus 4.7: 62.6 (#20)
- GLM-5.3: 58.3 (#34)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| GPQA Diamond | 90.2% | 90.9% |
| SimpleQA Verified | 51.7% | 41% |
| LMArena Expert | 1521 | 1512 |
| Humanity's Last Exam | 36.2% | — |
| Vectara Hallucination Rate | 12% | — |

## Multimodal

- Claude Opus 4.7: 41.5 (#29)
- GLM-5.3: —

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| LMArena Vision | 1317 | — |
| Blueprint-Bench 2 | 24.5% | — |
| Furniture Assembly | 33.3% | — |
| LMArena Document | 1495 | — |

## Multilingual

- Claude Opus 4.7: 57.5 (#9)
- GLM-5.3: 55.9 (#27)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1481 | 1457 |
| LMArena Chinese | 1530 | 1523 |
| LMArena French | 1505 | 1499 |
| LMArena German | 1494 | 1505 |
| LMArena Japanese | 1472 | 1438 |
| LMArena Korean | 1466 | 1478 |
| LMArena Russian | 1494 | 1460 |
| LMArena Spanish | 1497 | 1444 |

## Instruction Following

- Claude Opus 4.7: 78.6 (#9)
- GLM-5.3: 77.8 (#15)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1498 | 1481 |

## Long Context

- Claude Opus 4.7: 46.1 (#24)
- GLM-5.3: 45.5 (#32)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1505 | 1485 |

## Writing & Preference

- Claude Opus 4.7: 75.3 (#8)
- GLM-5.3: 75.9 (#6)

| Benchmark | Claude Opus 4.7 | GLM-5.3 |
|---|---|---|
| LMArena Text | 1491 | 1473 |
| LMArena Creative Writing | 1486 | 1459 |
| EQ-Bench Creative Writing | 1914 | 2075 |
| LMArena Multi-Turn | 1506 | 1473 |
| EQ-Bench 4 | 1311 | — |

## FAQ

### Is Claude Opus 4.7 better than GLM-5.3?

Claude Opus 4.7 is the stronger model overall, scoring 58.4 to 54.6 on the Noometry Index. GLM-5.3 costs 4.7× less per token, which makes it the better buy when Claude Opus 4.7's lead doesn't matter for your workload.

### Which is cheaper, Claude Opus 4.7 or GLM-5.3?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Claude Opus 4.7 lists at $5 and $25.

### Is Claude Opus 4.7 or GLM-5.3 better for coding?

They score almost the same on coding (59.9 vs 59.0); test both on your own repository before choosing.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do Claude Opus 4.7 and GLM-5.3 share?

38 benchmarks have published results for both models. Claude Opus 4.7 has 66 scored results on Noometry and GLM-5.3 has 41.